Pith. sign in

Paper Citation Record · LEDGER

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2512.15432.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2512.15432 v2

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T15:50:20.572239Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b628202-4280-4aee-8c8d-de49a9b3cc19 · outbound

This paper cites Digital twins: A survey on enabling technologies, challenges, trends and future prospects,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Digital twins: A survey on enabling technologies, challenges, trends and future prospects,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.188888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.188888Z digest=sha256:fc5d63d6379de8db30e75585c02ae2a3e6040752f095ad4deea2d2ffcf51a702

Observation 5b5b1c05-e52b-4cd6-866d-2670c3e1828b · outbound

This paper cites Network digital twin: Concepts and reference architecture,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Network digital twin: Concepts and reference architecture,

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.269872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.269872Z digest=sha256:682fc68369f1858b9b26b8544b53c255e0cf4ec37ccf06c76a71b766d0084029

Observation de0fe292-107b-4be1-8bba-9cc49386d441 · outbound

This paper cites Self-similarity in world wide web traffic: evidence and possible causes,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Self-similarity in world wide web traffic: evidence and possible causes,

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.328178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.328178Z digest=sha256:ecdd974d1faa3f5c3d654ed8cb1e15c361b486053d98ee2e62519fa83297a7c8

Observation f42d17f5-6a45-459f-aaa2-7db3bf7abbb8 · outbound

This paper cites Feasibility of state space models for network traffic generation,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Feasibility of state space models for network traffic generation,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.421848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.421848Z digest=sha256:0cf3744f718ac4800bf3054056cb3c9edcdd081fcb744707a22a1b62693d1264

Observation c8ab1ac4-0b9f-447f-a200-2aa5c1a5d841 · outbound

This paper cites Using GANs for sharing networked time series data: Challenges, initial promise, and open questions,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Using GANs for sharing networked time series data: Challenges, initial promise, and open questions,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.513033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.513033Z digest=sha256:7826f9bac3d59aa1a12d8fe3cc5bca8c1ba02773489cdc4e2a83033d3f91820f

Observation f9a6e4f6-c822-467c-a1e4-ab7a28908934 · outbound

This paper cites Mobile user traffic generation via multi-scale hierarchical GAN,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Mobile user traffic generation via multi-scale hierarchical GAN,

Reference 6

Resolution
verified exact
doi, observed 2026-08-03T15:53:32.350514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-03T15:50:19.602815Z digest=sha256:f356eb1f652a31ece2cabd3ed6bd39ae1d308f6c0cb40f37d4e0305a151e96ce

Observation 9c061e61-4b1b-46fd-8539-c56f9c2ad02d · outbound

This paper cites Generative deep learning for internet of things network traffic generation,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Generative deep learning for internet of things network traffic generation,

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.659244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.659244Z digest=sha256:89c21674dc08d6b53c2a62a1c825e7a04887c05bb35b7b8360da073216084407

Observation 340e7405-f1a8-49fa-b692-cdec3f3cd4d5 · outbound

This paper cites NeCSTGen: An ap- proach for realistic network traffic generation using deep learning,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins NeCSTGen: An ap- proach for realistic network traffic generation using deep learning,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.726682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.726682Z digest=sha256:b7560366454e4633e8f76f1e4d261cd23eb8a971659a2df6413546fd5220dc09

Observation 0af14b72-a77e-443c-83a6-bf306f577e86 · outbound

This paper cites TrafficGPT: Breaking the Token Barrier for Efficient Long Traffic Analysis and Generation.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins TrafficGPT: Breaking the Token Barrier for Efficient Long Traffic Analysis and Generation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.777788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.777788Z digest=sha256:d2a63bb544896e66801a80837966121936fba16ec70d60e09b12f6648e79f4f4

Observation 03ebdb0d-3ca7-4d97-a758-8f2cb778921c · outbound

This paper cites IP traffic generator based on hidden Markov models,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins IP traffic generator based on hidden Markov models,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.843701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.843701Z digest=sha256:9157ae948e92f9799a375e4f7a1d4ce62fac167d621f9c218e2b6077f7f4e180

Observation 3f663a96-ba66-4c83-bffa-f2ba1fc51267 · outbound

This paper cites Characterization of encrypted and VPN traffic using time-related,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Characterization of encrypted and VPN traffic using time-related,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.927765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.927765Z digest=sha256:9757e6bab086fdb35e369f37cc19c1ebe1bba072549408681351f058db72c692

Observation e98b8198-aad1-45de-96a3-7a9918ad180c · outbound

This paper cites A tutorial on hidden markov models and selected applica- tions in speech recognition,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins A tutorial on hidden markov models and selected applica- tions in speech recognition,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:19.985800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:19.985800Z digest=sha256:357dcaf4ba0a3fdcc0253b6c2f1fbea55d001e40bb685f8aad28c38ff5657ff2

Observation 27f5517b-4101-43e3-b2ac-19bced850d7c · outbound

This paper cites hmmlearn: Hidden markov models in python,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins hmmlearn: Hidden markov models in python,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.063663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.063663Z digest=sha256:2762aa3144e4a1dfb9320b5d670a33b4e053b1ba9cc36f49fd0aaa4af8062cd5

Observation c6f2b3bd-9565-424b-9bb5-05a66d098ec1 · outbound

This paper cites On the self-similar nature of ethernet traffic (extended version),.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins On the self-similar nature of ethernet traffic (extended version),

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.143741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.143741Z digest=sha256:7096f6b57ed9e68120de06d492189479641a045a42c61ceb27464cefb4bdd3f2

Observation 40024c3e-ad41-4e06-bad9-588715819ea3 · outbound

This paper cites State aware traffic generation for real-time network digital twins,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins State aware traffic generation for real-time network digital twins,

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.202817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.202817Z digest=sha256:03e436c1f66566713f12ba997444fdcebbb4900c00a9ac6557d369cb1cc89fe5

Observation 4cc666f9-c41d-4e43-a71b-98b3bd973a7c · outbound

This paper cites Robust statistical modeling using the t distribution,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Robust statistical modeling using the t distribution,

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.288431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.288431Z digest=sha256:8cc52c1f5bf1ab7fff81f5ebfb7a4a74e559f0614c99506032d307e4664d54a6

Observation 39999520-6152-4a1c-aa1a-3bad49ac7d66 · outbound

This paper cites Time-series generative adversarial networks,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Time-series generative adversarial networks,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.343738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.343738Z digest=sha256:31dc7ea0aaa333f9201971fd4c31e1b3e9f90db5104d27aff27deafea594d252

Observation f73eb890-eccb-4252-a15e-22ffd2d604f3 · outbound

This paper cites Wide area traffic: the failure of poisson modeling,.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Wide area traffic: the failure of poisson modeling,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.509484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.509484Z digest=sha256:8275bdc97d2ae7d93d8b3bd1c90b0565fcd2f273dca0416d5eca6abc95239863

Observation 211a92f9-6c49-44d6-ba4b-8e23aa5f9380 · outbound

This paper cites Computational Optimal Transport.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Computational Optimal Transport

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.572239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.572239Z digest=sha256:8a984b5488bf4c2d949e2aa5fac8ce53663c1ac7b94db259ea96fac77bfbed3b

Observation 7b260597-f4ec-46ce-a3b6-74bad75fcb1a · outbound

This paper cites Available: https://proceedings.neurips.cc/paper files/ paper/2019/file/c9efe5f26cd17ba6216bbe2a7d26d490-Paper.pdf.

Packet-Level Traffic Modeling with Heavy-Tailed Payload and Inter-Arrival Distributions for Digital Twins Available: https://proceedings.neurips.cc/paper files/ paper/2019/file/c9efe5f26cd17ba6216bbe2a7d26d490-Paper.pdf

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-03T15:50:20.421065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:50:20.421065Z digest=sha256:73e58a73e651665c35b2600665f18eaa81955121212fa2602665ed31a64e163f

Pith citing papers

No inbound Pith citation observations are available.